{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://raw.githubusercontent.com/Qiskit/qiskit-tutorials/master/images/qiskit-heading.png\" alt=\"Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook\" width=\"500 px\" align=\"left\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## _*Qubit Spectroscopy*_ \n",
    "\n",
    "\n",
    "***\n",
    "### Contributors\n",
    "Naoki Kanazawa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "In this tutorial, we learn how to conduct qubit spectroscopy using OpenPulse. The OpenPulse frontend enables us to control qubits at the level of microwave pulses, and allows for controlling their driving frequency as well. This increases the degree of freedom in controlling quantum state. Qubit \"chevron\" pattern may be a good example of showing the capability of OpenPulse, in which we measure qubit Rabi oscillation for various microwave frequencies. As the frequency detuning increases, it is expected to observe faster oscillations with reduced excited state population.\n",
    "\n",
    "\n",
    "**Contents**\n",
    "\n",
    "[Qubit Spectroscopy](#sect1)\n",
    "\n",
    "\n",
    "### References\n",
    "[1] David C. McKay *et al.*, Qiskit Backend Specifications for OpenQASM and OpenPulse Experiments. https://arxiv.org/abs/1809.03452"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code imports\n",
    "=============="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from qiskit import IBMQ, pulse\n",
    "import qiskit.pulse.pulse_lib as pulse_lib\n",
    "from qiskit.compiler import assemble"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Qubit Spectroscopy\n",
    "\n",
    "In this tutorial, we use a quantum computing system with `open_pulse` enabled and `meas_level=2` is activated. We measure Rabi oscillation for various frequency detunings $\\Delta f_i \\in $ `freq_bounds`. At each driving frequency $f_d = f_q + \\Delta f_i$, where $f_q$ is the dressed frequency of qubit, we measure the excited state population of target `qubit` after irradiation of driving pulses with different pulse duration $T \\in $ `duration_bounds`.\n",
    "\n",
    "You can refer to [qiskit iqx tutorials](https://github.com/Qiskit/qiskit-iqx-tutorials) for the details about creation of pulse `Schedule`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Target qubit\n",
    "qubit = 0\n",
    "\n",
    "# Number of experiments\n",
    "num_duration = 31\n",
    "num_drive_freq = 21\n",
    "\n",
    "# Range of frequency detuning sweep in GHz\n",
    "freq_bounds = -0.01, 0.01\n",
    "\n",
    "# Range of duration sweep in the unit of dt\n",
    "duration_bounds = 30, 300\n",
    "\n",
    "# Rabi pulse spec\n",
    "drive_amplitude = 0.02\n",
    "drive_sigma = 3\n",
    "drive_risefall = 12\n",
    "\n",
    "# Number of shot\n",
    "rabi_shots = 512"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading backend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "IBMQ.load_account()\n",
    "ibmq_provider = IBMQ.get_provider(\n",
    "    hub='provide_your_hub_name_here',\n",
    "    group='provide_your_group_name_here',\n",
    "    project='provide_your_project_name_here'\n",
    ")\n",
    "backend = ibmq_provider.get_backend(\n",
    "    'ibmq_poughkeepsie'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "system = pulse.PulseChannelSpec.from_backend(backend)\n",
    "\n",
    "config = backend.configuration()\n",
    "defaults = backend.defaults()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cmd_def = pulse.CmdDef.from_defaults(defaults.cmd_def, defaults.pulse_library)\n",
    "\n",
    "measure = cmd_def.get('measure', qubits=config.meas_map[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating pulse `Schedule`.\n",
    "\n",
    "Each `Schedule` comprises a Rabi pulse with different pulse duration followed by measurement pulse and acquisition. These `Schedule`s are used for all driving frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Frequency sweep centered at resonance frequency\n",
    "df_lb, df_ub = freq_bounds\n",
    "f_reso = defaults.qubit_freq_est[qubit]\n",
    "freqs = np.linspace(f_reso + df_lb, f_reso + df_ub, num_drive_freq, dtype=float)\n",
    "\n",
    "# Time sweep\n",
    "duration_lb, duration_ub = duration_bounds\n",
    "durations = np.linspace(duration_lb, duration_ub, num_duration, dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "schedules = []\n",
    "for duration in durations:\n",
    "    rabi_pulse = pulse_lib.gaussian_square(duration=duration,\n",
    "                                           amp=drive_amplitude,\n",
    "                                           sigma=drive_sigma,\n",
    "                                           risefall=drive_risefall,\n",
    "                                           name = 'drive_t_%d' % duration)\n",
    "\n",
    "    schedule = pulse.Schedule(name='duration_%3d' % duration)\n",
    "    schedule = schedule | rabi_pulse(system.qubits[qubit].drive)\n",
    "    schedule = schedule | measure << schedule.duration + defaults.buffer\n",
    "\n",
    "    schedules.append(schedule)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x864 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedules[0].draw(channels_to_plot=[system.qubits[0].drive, system.qubits[0].measure], label=True, plot_range=(0, 200), scaling=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedules[5].draw(channels_to_plot=[system.qubits[0].drive, system.qubits[0].measure], label=True, plot_range=(0, 200), scaling=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedules[10].draw(channels_to_plot=[system.qubits[0].drive, system.qubits[0].measure], label=True, plot_range=(0, 200), scaling=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating `PulseQobj`s.\n",
    "Qobj is created for each driving frequency. Each qobj comprises several `Schedule`s for pulse duration sweep."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "qobj_freq_sweeps = []\n",
    "for freq in freqs:\n",
    "    lo_settings = defaults.qubit_freq_est.copy()\n",
    "    lo_settings[qubit] = freq\n",
    "    \n",
    "    qobj_freq_sweeps.append(assemble(schedules, backend,\n",
    "                                     meas_level=2,\n",
    "                                     meas_return='single',\n",
    "                                     shots=rabi_shots,\n",
    "                                     qubit_lo_freq=lo_settings))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Warning: this sends a lot of jobs\n",
    "=======\n",
    "\n",
    "Uncomment the below cell to run the experiment. Make sure your token has enough capability to run these jobs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# jobs = []\n",
    "# for qobj in qobj_freq_sweeps:\n",
    "#     jobs.append(backend.run(qobj))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.036901 GHz || job_id=\"5d6e8d65750f40001950b72c\"\n",
      "5.037901 GHz || job_id=\"5d6e8d67a022f60018990b7e\"\n",
      "5.038901 GHz || job_id=\"5d6e8d6d750f40001950b72e\"\n",
      "5.039901 GHz || job_id=\"5d6e8d6f017bdb0019330055\"\n",
      "5.040901 GHz || job_id=\"5d6e8d69a022f60018990b80\"\n",
      "5.041901 GHz || job_id=\"5d6e8d6b017bdb0019330053\"\n",
      "5.042901 GHz || job_id=\"5d6e8d6da022f60018990b82\"\n",
      "5.043901 GHz || job_id=\"5d6e8d6d61b82a0019a82c75\"\n",
      "5.044901 GHz || job_id=\"5d6e8d73750f40001950b730\"\n",
      "5.045901 GHz || job_id=\"5d6e8d7019f20e00187493e2\"\n",
      "5.046901 GHz || job_id=\"5d6e8d719dbedc0018dd21c6\"\n",
      "5.047901 GHz || job_id=\"5d6e8d749dbedc0018dd21c8\"\n",
      "5.048901 GHz || job_id=\"5d6e8d7319f20e00187493e4\"\n",
      "5.049901 GHz || job_id=\"5d6e8d75747e970019d4e802\"\n",
      "5.050901 GHz || job_id=\"5d6e8d76a022f60018990b84\"\n",
      "5.051901 GHz || job_id=\"5d6e8d78a022f60018990b86\"\n",
      "5.052901 GHz || job_id=\"5d6e8d79017bdb0019330057\"\n",
      "5.053901 GHz || job_id=\"5d6e8d7a750f40001950b732\"\n",
      "5.054901 GHz || job_id=\"5d6e8d7b017bdb0019330059\"\n",
      "5.055901 GHz || job_id=\"5d6e8d7d017bdb001933005b\"\n",
      "5.056901 GHz || job_id=\"5d6e8d7ef248bf0018b71205\"\n"
     ]
    }
   ],
   "source": [
    "for job, freq in zip(jobs, freqs):\n",
    "    print('%f GHz || job_id=\"%s\"' % (freq, job.job_id()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n",
      "JobStatus.DONE\n"
     ]
    }
   ],
   "source": [
    "for job in jobs:\n",
    "    print(job.status())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analyze the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = [job.result() for job in jobs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "chevron_data = np.zeros((num_duration, num_drive_freq))\n",
    "\n",
    "for ind_freq in range(num_drive_freq):\n",
    "    for ind_duration in range(num_duration):\n",
    "        counts = results[ind_freq].get_counts('duration_%3d' % durations[ind_duration])\n",
    "        excited_pop = 0\n",
    "        for bits, count in counts.items():\n",
    "            excited_pop += count if bits[::-1][qubit] == '1' else 0\n",
    "        chevron_data[ind_duration, ind_freq] = excited_pop/rabi_shots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Qubit 0')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x400 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_freq = freq_bounds[0] * 1e3\n",
    "max_freq = freq_bounds[1] * 1e3\n",
    "\n",
    "min_time = duration_bounds[0] * config.dt\n",
    "max_time = duration_bounds[1] * config.dt\n",
    "\n",
    "plt.figure(figsize=(5, 4), dpi=100)\n",
    "\n",
    "plt.imshow(chevron_data,\n",
    "           extent=[min_freq, max_freq, min_time, max_time],\n",
    "           cmap='jet',\n",
    "           origin='lowest', aspect='auto', vmin=0, vmax=1)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Frequency detuning, MHz', fontsize=20)\n",
    "plt.ylabel('Drive pulse duration, ns', fontsize=20)\n",
    "plt.title('Qubit %s' % qubit, fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we cut a cross section at certain pulse duration $T$, we can observe a peak centered at backend default frequency `qubit_freq_est`. The dashed line corresponds to this calibrated frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fb3b5cc9c88>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(freqs, chevron_data[3, :], marker=\"o\", label='$T$ = %.1f ns' % (durations[3] * config.dt))\n",
    "plt.axvline(defaults.qubit_freq_est[qubit], color='black', linestyle='dashed')\n",
    "plt.xlim(freqs[0], freqs[-1])\n",
    "plt.ylim(0, 1)\n",
    "plt.xlabel('Frequency, GHz', fontsize=20)\n",
    "plt.ylabel('Excited state population', fontsize=20)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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